Circular RNA-Related CeRNA Network and Prognostic Signature for Patients with Osteosarcoma

Advances in prognostic models for osteosarcoma risk

The risk prognosis model is a statistical model that uses a set of features to predict whether an individual will develop a specific disease or clinical outcome. It can be used in clinical practice to stratify disease severity and assess risk or prognosis. With the advancement of large-scale second-generation sequencing technology, along Prognosis models for osteosarcoma are increasingly being developed as large-scale second-generation sequencing technology advances and clinical and biological data becomes more abundant. This expansion greatly increases the number of prognostic models and candidate genes suitable for clinical use. This article will present the predictive effects and reliability of various prognosis models, serving as a reference for their evaluation and application.

Antigen processing and presentation-related signature-derived BNIP3 is a novel oncogene and immunotherapy determinant in osteosarcoma based on machine learning and in vitro validation

BACKGROUND

In recent decades, osteosarcoma has remained the most prevalent kind of malignant tumor. An important and crucial factor in immunotherapy is antigen processing and presentation (APP). The specific functions and pathogenic processes of APP in osteosarcoma have not, however, been studied.

METHODS

Patients with osteosarcoma were divided into groups using APP-related genes. Machine learning was used to further build the APP-related score. Investigated in-depth were the prognostic relevance of the score, mutation features, immunological aspects, and pharmacological prediction performance. Investigations of the prognostic utility, immunological traits, drug prediction effectiveness and immunotherapy prediction of BNIP3 were performed in-depth.

RESULTS

Investigations by cell counting kit-8, Transwell and 5-ethynyl-2-deoxyuridine (EdU) demonstrated that BNIP3 is an osteosarcoma tumor accelerator. The osteosarcoma gene BNIP3 may promote macrophage migration. The APP-related score shows potential for clinical use.

CONCLUSIONS

It was anticipated that more in vitro and in vivo studies would confirm BNIP3's tumorigenic and immunogenic processes in osteosarcoma.

METTL3-mediated m6A modification of circRNF220 modulates miR-330-5p/survivin axis to promote osteosarcoma progression

BACKGROUND

Circular RNAs (circRNAs) play a crucial role in regulating various physiological processes. However, the precise regulatory mechanisms of circRNF220s in osteosarcoma (OS) are not well understood.

METHODS

The abundances of circRNF220, miR-330-5p, and survivin were determined using qRT-PCR. To assess the m6A accumulation in circRNF220, a methylated RNA immunoprecipitation (Me-RIP) assay was conducted. Cellular multiplication, motility, and invasion were examined using the cell Counting Kit-8 (CCK-8), EdU, colony formation, Transwell, and wound-healing assays. The binding relationships were measured through RNA immunoprecipitation (RIP) and luciferase reporter assays. In vivo functionality was assessed using xenograft models.

RESULTS

CircRNF220 was identified as being overexpressed in both OS cells and tissues. In vitro experiments demonstrated that silencing circRNF220 impeded the proliferation, invasion, and motility of OS cells. Similarly, in vivo studies confirmed that downregulating circRNF220 inhibited the growth of OS. Further mechanistic investigations unveiled that METTL3-modulated circRNF220 regulated the progression of OS by upregulating survivin expression through acting as a sponge for miR-330-5p.

CONCLUSION

The modulation of METTL3-regulated circRNF220 has been found to promote the progression of OS by modulating the miR-330-5p/survivin axis. This novel finding suggests a potentially unique approach to managing OS.

Hsa_circ_0020378 targets miR-556-5p/MAPK1 to regulate osteosarcoma cell proliferation and migration

Osteosarcoma (OS) is still a disorder threatening children life. A growing number of evidences highlights the role of circular RNAs (circRNAs) during OS malignancy. Herein, we aimed to address the pathological contribution of the unrecognized circ_0020378 to OS progression. Analysis of the expression of circ_0020378, miR-556-5p, and MAPK1 in OS tissues and cells was performed using RT-qPCR or western blotting. CCK8, colony formation assays, and Tranwell migration assays were adopted to assess the OS cell viability, clone formation ability and migration. Tumor xenograft mouse model was used to assess the in vivo function of circ_0020378. The relationship between miR-556-5p and circ_0020378 or MAPK1 was discovered using luciferase reporter assays and RNA binding protein immunoprecipitation tests. In OS tissues and cells, circ_0020378 and MAPK1 were significantly elevated, although miR-556-5p expression exhibited a different pattern. Circ_0020378 silence attenuated OS cell proliferation, colony formation ability and migration in vitro, and retarded tumor growth in vivo. MiR-556-5p was targeted by circ_0020378. Furthermore, miR-556-5p inhibitor promoted the OS cell proliferation and migration, while this promoted malignant actions of OS cells were abrogated by circ_0020378 silence. Additionally, miR-556-5p directly bound to MAPK1, and MAPK1 silence exerted its inhibitory effect on OS cell proliferation and migration, and yet the inhibition was offset by miR-556-5p inhibitor. Circ_0020378 acts as a novel tumor promoter that controls OS growth by miR-556-5p/MAPK1 axis, suggesting circ_0020378/miR-556-5p/MAPK1 might be a novel target for OS intervention.

MLLT11-TRIL complex promotes the progression of endometrial cancer through PI3K/AKT/mTOR signaling pathway

Endometrial cancer (EC) is a gynecological malignant tumor characterized by high incidence. EC occurrence and development are regulated by numerous molecules and signal pathways. There is a need to explore key regulatory molecules to identify potential therapeutic targets to reduce the incidence of EC. Treatment by targeting a single molecule is characterized by poor efficacy owing to the development of resistance and significant side effects. The current study explored potential candidates in EC by integrating bioinformatics analysis and in vivo and in vitro experimental validation to circumvent the limitation of low efficacy of currently used molecules. Molecular dynamics simulations provide details at the molecular level of intermolecular regulation. In the current study, MLLT11 and TRIL were identified as important regulatory molecules in EC. The two molecules formed a heteromultimer by binding to AKT protein, which induced its phosphorylation of threonine at position 308. Ultimately, the complex stimulates PI3K/AKT/mTOR signaling pathway, a pivotal pathway in tumors. The findings of the current study show a novel complex, MLLT11-TRIL, which can act as AKT protein agonist, thus inducing activity of PI3K/AKT/mTOR signaling pathway. Targeting MLLT11 and TRIL simultaneously, or blocking the formation of the MLLT11-TRIL complex, can abrogate progression of EC.

Enhanced MCM5 Level Predicts Bad Prognosis in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a fatal heterogeneous hematologic malignancy. There is an urgent need to identify potential biomarkers to better classify sufferers with bad outcomes that might need more advanced treatment. The objective of this study was to investigate prognostic indicators that predict the outcome of sufferers with AML. The datasets of AML sufferers including mRNA sequencing data and clinical information were acquired from GEO datasets (GSE38865) and TCGA datasets. Kaplan–Meier curves and Cox regression analysis to screen genes correlated to survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses biological process analysis were utilized in verifying the function of various genes. Sufferers with elevated MCM5 level exhibited a worse prognosis, according to the survival analysis. It was indicated through multivariate and univariate analysis that MCM5 level was an independent adverse prognostic element for over survival in AML sufferers based on GEO and TCGA datasets. Meanwhile, MCM5 level in AML samples was higher than in normal samples. Additionally, it was indicated through PPI network and functional enrichment analyses that through accelerating cell cycle and DNA replication, MCM5 promoted AML progression. In conclusions, MCM5 level was an independent poor prognostic element in AML sufferers based on GEO and TCGA datasets. This is the first time that MCM5 is reported to be a biomarker of poor prognosis in AML.

Relationship between M6A methylation regulator and prognosis in patients with hepatocellular carcinoma after transcatheter arterial chemoembolization

Background

Patients with mid-stage HCC (hepatocellular carcinoma) may benefit from transcatheter arterial chemoembolization (TACE). However, patient efficacy varies widely, and the detailed assessment index is unknown. The most general methylation alteration in mRNA (Messenger RNA), N6-methyladenosine (m6A), is controlled by the m6A regulator, which is associated with the emergence of tumors. To include the molecular causes of cancer, competition with ceRNA (endogenous RNA) networks is crucial. However, the exact processes they contribute to TACE HCC remain uncertain. The purpose of this study was tantamount to investigating the possible function of ceRNA networks and m6A regulators in patients with TACE HCC.

Methods

Genes Associated with m6A were discovered using the TACE GEO (Gene Expression Omnibus) dataset. An additional estimate of M6A-associated DEGs (differentially expressed genes) was used to create a predictive response model, which is required. LncRNA-miRNA and miRNA-mRNA interactions were then predicted, the regulatory ceRNA network was set up using Cytoscape software, and target genes were identified using GEPIA online analysis. The connection between immunological checkpoints, immune cell marker genes, and target genes for immune cells was also examined.

Results

The detection of 4 m6A-associated DEGs, the development and evaluation of 2 Machine learning models, and the development of risk models that accurately predicted the response rate of specific patients. Additionally, we obtained two miRNAs (micro RNAs)and six lncRNAs (Long non-coding RNAs), forming an 8-pair ceRNA network, and the target gene LRPPRC deletion of one copy number and gene expression was highly correlated with the amount of Tregs immune cells. LRPPRC was related positively with NRP1, IRF5, and ITGAM and negatively with CCR7 and CD8B among immune cell marker genes. We also discovered that LRPPRC correlates positively with immune checkpoint CD274 cells.

Conclusion

The response of HCC patients to TACE therapy may be predicted using a model based on four gene expression data. We also developed a ceRNA network for TACE HCC related to m6A, which offered suggestions for more research into its molecular processes and possible prognostic indicators.